The indicators and analysis presented in this bulletin are based on responses from the new voluntary fortnightly business survey, which captures businesses responses on how their turnover, workforce prices, trade and business resilience have been affected in the two week reference period. These data relate to the period 6 April 2020 to 19 April 2020.

This page is no longer updated. It has been superseded by the Business insights and impacts on the UK economy dataset page (see link in Notices). It contains comprehensive weighted datasets for Wave 7 onwards. All future BICS datasets will be available there. The datasets on this page include mainly unweighted responses from the voluntary fortnightly business survey, which captures businesses’ responses on how their turnover, workforce prices, trade and business resilience have been affected in the two-week reference period, up to Wave 17.

Weighted estimates from the voluntary fortnightly Business Insights and Conditions Survey (BICS) about financial performance, workforce, prices, trade, and business resilience. These are official statistics in development.

Abstract copyright UK Data Service and data collection copyright owner.

The Business Insights and Conditions Survey (BICS, formerly the Business Impact of COVID-19 Survey) is a voluntary fortnightly survey of businesses developed to deliver timely indicators to help understand the impact of the coronavirus pandemic (COVID-19). The scope of the survey has been expanded to explore other economic-related issues such as the European Union transition period (Brexit). The survey captures businesses responses on how their turnover, workforce, prices, trade and business resilience have been affected in the two week reference period.

The data should be treated with caution as results reflect the characteristics of those who responded and not necessarily the wider business population. Comparison of the proportions of businesses' trading status between waves should be treated with caution because of the voluntary nature of the survey, the difference in response rates and dependency on those businesses that only responded in particular waves. These data should not be used in place of official statistics. The survey was designed to give an indication of the impact of the coronavirus on businesses and a timelier estimate than other surveys. The latest publications from the survey can be found on the ONS Business Services webpage.
Linking to other business studiesThese data contain IDBR reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.
Latest edition information
For the twenty-eighth edition (November 2024), data and documentation for Wave 115 have been added to the study.
Main Topics:

BICS covers questions relating to:

• financial performance of the business
• operational performance of the business
• other financial or operational issues

A full list of variables available for each wave is included in the BICS Variable Catalogue, Questionnaires and Data Dictionaries, which are part of the study documentation.

Textual analysis of responses from the Business Impacts of Coronavirus (COVID-19) Survey (BICS), providing further insights into the experiences of individual businesses.

The indicators and analysis presented in this bulletin are based on responses from the new voluntary fortnightly business survey, which captures business' views on impact on turnover, workforce prices, trade and business resilience

Licensees and Registrants Fleet Information dataset contains information about active vehicles of approved BIC licensees and registrants. This data is partially collected from the application submitted to the commission by licensees and registrants. The majority of data points are collected from licensees and registrants via the Vehicle Management Portal. Business Integrity Commission maintains this dataset, updating it quarterly. Each row of data contains information about an active vehicle registered at BIC, including BIC plate number, vehicle year, vehicle model, vehicle make, engine year and so on.

BIC issued violations dataset includes violations issued by Business Integrity Commission for companies operating in the trade waste industry. Business Integrity Commission maintains this dataset, updating it quarterly. Each row of data contains information about a violation issued by BIC to an approved or unlicensed company in the trade waste industry. These violations are adjudicated within the Office of Administrative Trials and Hearings (OATH).

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

BIC Complaints Inquiries dataset contains information on all waste hauling complaints/inquiries BIC received. Each row of data contains information about a complaint or inquiry, including source of complaint/inquiry, nature of complaint/inquiry, company name, geographic location, total response time, and complaint/inquiry disposition.

Business Integrity Commission maintains this dataset (Trade Waste Enforcement Unit), updating it quarterly.

The Can-BICS metrics are dissemination-area level measures of the cycling environment based on the quantity and quality of cycling infrastructure (high, medium, and low comfort classifications). The metrics were developed based on a classification of OpenStreetMap (OSM) data using Can-BICS infrastructure categories as consistent criteria and data acquired on January 25, 2022. The spatial unit for the Can-BICS metrics is a 1 km circular buffer around the population-weighted DA centroid. NOTE: all postal codes within the same dissemination area have been assigned the same value. Some mathematical operations are therefore not valid for aggregating postal code values. There are two summary metrics for each buffer area that are assigned to each dissemination area. The Can-BICS continuous metric is a weighted sum of high-comfort kms (×3), medium-comfort kms (×2), and low-comfort kms (×1) within the buffer, normalized by the land area (km2) within each buffer. The Can-BICS categorical metric is 5 categories assigned using K-medians clustering of the continuous measure. Category 1 represents the lowest level of infrastructure, and Category 5 represents the highest level of infrastructure.Can-BICS national data were developed by Dr. Meghan Winters, Dr. Trisalyn Nelson, Dr. Kevin Manaugh, Jeneva Beairsto, Dr. Colin Ferster, Karen Laberee, with help from Jaimy Fischer, and Moreno Zanotto. Data by OpenStreetMap contributors (2022). Please refer to the supporting documentation.

This statistic shows the usage frequency of BIC Comfort disposable razors / shavers in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 3.2 million Americans used BIC Comfort disposable razors / shavers 5 or more times within a week in 2020.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This statistic shows the usage frequency of BIC Soleil disposable razors / shavers in the United States in 2020. The data has been calculated by Statista based on the U.S. Census data and Simmons National Consumer Survey (NHCS). According to this statistic, 1.04 million Americans used BIC Soleil disposable razors / shavers 5 or more times within a week in 2020.

This dataset provides information about the number of properties, residents, and average property values for Bic Drive cross streets in Milford, CT.

Weighted estimates from the voluntary fortnightly business survey (BICS) about financial performance, workforce, prices, trade, and business resilience in a timeseries format.

Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal or repeated measures. This paper develops an Expectation-Maximization algorithm for discriminant analysis and classification with matrix-variate t-distributions. The methodology shows promise on simulated datasets or when applied to the forensic matching of fractured surfaces or the classification of functional Magnetic Resonance, satellite or hand gestures images.

Summed across participants AICc and BIC, values were converted to delta values.

This graph indicates the sales volume of the French group Bic in 2019, by product category and in million units. In 2019, almost 7 billion paper products were sold by Bic in worldwide.